Optimal Power Scheduling for Remote State Estimation: A Quantitative and Analytical Approach
Yao Li, Cailian Chen, Shanying Zhu, Xinping Guan · 2019
In this paper, problem of optimal sensor scheduling with limited power resources is considered. For a discrete-time linear process, we consider a more practical scenario where forward-error-correcting(FEC) coding scheme is utilized. An approximate linearized communication model is introduced to formulate the relationship between the consumption of power and successful-decoding-probability. Different from the present literatures, it is our first attempt to propose an analytical method to figure out the optimal off-line schedules under continuous power space. Numerical examples and essential proofs are provided to demonstrate and highlight the correctness of proposed ideas.